Search

Introduction Life cycle costing is an important management tool that takes into account the implications of planning, acquiring, operating, maintaining, and disposing of an asset during its complete life cycle. A major hindrance to the procurement of expensive equipment in developing countries is the lack of a reliable framework combining and integrating all the equipment life cycle aspects into procurement process.

The wide-ranging use of renewable energy sources (RES) in the modern era leads to the association of distributed non-conventional energy resources in contrary to large-scale and localized conventional non-renewable sources. The prevalent use of distributed sources produces various Power-Quality issues. A thorough review of the literature provides numerous approaches for Power Quality (PQ) improvements; however, most techniques can improve only a few PQ problems. The new technical challenges like power loss, stability, reliability and power quality (PQ) issues are observed in present micro grid scenario. In this regard, this research work is an attempt to address PQ improvement in a three-phase realistic complex micro grid (integration of three simple micro grids to the point of common coupling. Improvement of various PQ factors for example sag/swell, unbalancing, power factor (Pf), total harmonic distortion (THD), communication delay and addition of impedance has been addressed in this research work. In this research article, a Kernel based Deep Auto Regressive Exogenous Output Neural Network (KDNARX) controller has been proposed and applied to improve power quality issues in a complex or realistic three phase complex micro grid (RTPCMG) in grid connected mode of operation. The RTPCMG is a combination of three simple grids with individual ratings of (4 kW, 4 kW and 6 kW). Photo voltaic cell, wind generator (WG), fuel cell (FC) and battery energy storage system (BESS) are the constituent distributed generators (DGs) for the proposed micro grid. The PQ improvement by application of proposed KDNARX controller to the DG inverter switching, has been overly tested in 12 different power quality issues under various operating conditions. The Kernel parameters are optimized by a new optimization technique called Cosine Chaotic PSO (CCPSO) algorithm. The results proved the strength of the new control technique ensuring PQ improvement and stability study of a three phase AC micro grid. Also, the potentiality of the new control scheme is compared with ANN and NARX and its superiority has been proved. Further, some case studies are validated through hardware in loop (HIL) environment thus justifying its real time implementation.

Coal mine tailings can lead to a range of environmental problems, including toxic metal contamination, soil erosion, acid mine drainage, and increased salinity. Mine spoils from coal mining activities accumulated as gob piles are difficult to reclaim due to constraints such as a steep slope, unsuitable pH, insufficient nutrient supply, metal toxicity, low water-holding capacity, and poor soil structure. We investigated the efficiency of low-cost amendments on coal gob spoils from Carthage Coal Field (CCF) in New Mexico in improving the quality of coal gob spoils. Gob spoil was incubated for 90 days with various rates of organic amendments such as biochar, compost, and a biochar–compost mix. Gob spoil quality parameters such as the pH, water-holding capacity, and total and plant-available nitrogen and phosphorus content of the gob spoil were measured over a period of 90 days. Both biochar and compost amendment led to a significant increase (40–60% for biochar and 70% for compost, p < 0.05) in water-holding capacity of the coal gob spoil. Plant-available nitrogen content increased from

This paper focuses on the distributed generation (DG) controller of a PV-based microgrid. An independent DG controller (IDGC) is designed for PV applications to improve Maximum-Power Point Tracking (MPPT). The Extreme-Learning Machine (ELM)-based MPPT method exactly estimates the controller’s reference input, such as the voltage and current at the MPP. Feedback controls employ linear PI schemes or nonlinear, intricate techniques. Here, the converter controller is an IDGC that is improved by directly measuring the converter duty cycle and PWM index in a single DG PV-based MG. It introduces a fast-learning Extreme-Learning Machine (ELM) using the Moore–Penrose pseudo-inverse technique and online sequential ridge methods for robust control reference (CR) estimation. This approach ensures the stability of the microgrid during PV uncertainties and various operational conditions. The internal DG control approach improves the stability of the microgrid during a three-phase fault at the load bus, partial shading, irradiance changes, islanding operations, and load changes. The model is designed and simulated on the MATLAB/SIMULINK platform, and some of the results are validated on a hardware-in-the-loop (HIL) platform.

T cell exhaustion limits antitumor immunity, but the molecular determinants of this process remain poorly understood. Using a chronic stimulation assay, we performed genome-wide CRISPR-Cas9 screens to systematically discover regulators of T cell exhaustion, which identified an enrichment of epigenetic factors. In vivo CRISPR screens in murine and human tumor models demonstrated that perturbation of the INO80 and BAF chromatin remodeling complexes improved T cell persistence in tumors. In vivo Perturb-seq revealed distinct transcriptional roles of each complex and that depletion of canonical BAF complex members, including Arid1a, resulted in the maintenance of an effector program and downregulation of exhaustion-related genes in tumor-infiltrating T cells. Finally, Arid1a depletion limited the acquisition of exhaustion-associated chromatin accessibility and led to improved antitumor immunity. In summary, we provide an atlas of the genetic regulators of T cell exhaustion and demonstrate that modulation of epigenetic state can improve T cell responses in cancer immunotherapy.

T cell exhaustion is a major impediment to antitumor immunity. However, it remains elusive how other immune cells in the tumor microenvironment (TME) contribute to this dysfunctional state. Here, we show that the biology of tumor-associated macrophages (TAMs) and exhausted T cells (Tex) in the TME is extensively linked. We demonstrate that in vivo depletion of TAMs reduces exhaustion programs in tumor-infiltrating CD8+ T cells and reinvigorates their effector potential. Reciprocally, transcriptional and epigenetic profiling reveals that Tex express factors that actively recruit monocytes to the TME and shape their differentiation. Using lattice light sheet microscopy, we show that TAM and CD8+ T cells engage in unique, long-lasting, antigen-specific synaptic interactions that fail to activate T cells but prime them for exhaustion, which is then accelerated in hypoxic conditions. Spatially resolved sequencing supports a spatiotemporal self-enforcing positive feedback circuit that is aligned to protect rather than destroy a tumor.

We report on the design and development of an introductory analytics course delivered to almost 10,000 undergraduate business students to date. One novel aspect of the course is its orientation to add analytics capabilities to a business student's toolbox, resulting in significant design and implementation implications. We anchored the course on three fundamental principles: maximizing learning, operating at scale, and a consistent experience for all learners. To enable a rigorous and valuable learning experience, the underlying course curriculum is based on the modified CRISP-DM (CRoss Industry Standard Process for Data Mining) framework. Bloom's taxonomy is applied to the course assessments to evaluate the depth of learning. The course is delivered in a hybrid mode, arguably the best combination of online and face-to-face delivery modes. In a naturally occurring experimental setting, the COVID-19 pandemic accelerated the evolution of the course and generated additional reinforcing lessons. We explore those lessons and suggest directions for further research.

Relapse of acute myeloid leukemia (AML) is highly aggressive and often treatment refractory. We analyzed previously published AML relapse cohorts and found that 40% of relapses occur without changes in driver mutations, suggesting that non-genetic mechanisms drive relapse in a large proportion of cases. We therefore characterized epigenetic patterns of AML relapse using 26 matched diagnosis-relapse samples with ATAC-seq. This analysis identified a relapse-specific chromatin accessibility signature for mutationally stable AML, suggesting that AML undergoes epigenetic evolution at relapse independent of mutational changes. Analysis of leukemia stem cell (LSC) chromatin changes at relapse indicated that this leukemic compartment underwent significantly less epigenetic evolution than non-LSCs, while epigenetic changes in non-LSCs reflected overall evolution of the bulk leukemia. Finally, we used single-cell ATAC-seq paired with mitochondrial sequencing (mtscATAC) to map clones from diagnosis into relapse along with their epigenetic features. We found that distinct mitochondrially-defined clones exhibit more similar chromatin accessibility at relapse relative to diagnosis, demonstrating convergent epigenetic evolution in relapsed AML. These results demonstrate that epigenetic evolution is a feature of relapsed AML and that convergent epigenetic evolution can occur following treatment with induction chemotherapy.

In this work, we find that CD8+ T cells expressing inhibitory killer cell immunoglobulin-like receptors (KIRs) are the human equivalent of Ly49+CD8+ regulatory T cells in mice and are increased in the blood and inflamed tissues of patients with a variety of autoimmune diseases. Moreover, these CD8+ T cells efficiently eliminated pathogenic gliadin-specific CD4+ T cells from the leukocytes of celiac disease patients in vitro. We also find elevated levels of KIR+CD8+ T cells, but not CD4+ regulatory T cells, in COVID-19 patients, correlating with disease severity and vasculitis. Selective ablation of Ly49+CD8+ T cells in virus-infected mice led to autoimmunity after infection. Our results indicate that in both species, these regulatory CD8+ T cells act specifically to suppress pathogenic T cells in autoimmune and infectious diseases.

Having established the significance of cardiovascular side-effects of anti-neoplastic drugs, present day cardio-oncology has forayed into newer territories buoyed by research into the multiple connections that exist between cardiovascular disease and cancer. An emerging concept of reverse cardio-oncology focuses on the heightened risk of cancer in patients with cardiovascular disease. Common mechanistics of cancer and heart failure (HF) like chronic inflammation and clonal haematopoesis as well as common predisposing factors like obesity and diabetes underline the relation between both cardiovascular disease and various cancers.This review discusses the potential magnitude of the problem, the underlying pathophysiological mechanisms and classification of this novel subject.